Andrew B Speer, Andrew P Tenbrink, Lauren J Wegmeyer, Caitlynn C Sendra, Mike Shihadeh, Sugandhjot Kaur
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In total, 180 independent samples of criterion correlations were examined, and 63 samples were analyzed containing correlations with convergent measures. Findings across the meta-analyses revealed that biodata inventories are one of the most predictive assessment methods available, but that the relationship with work outcomes differs by construct domain and scoring method. Empirically scored overall composite scales had superior criterion-related validity (ρ = .44) to rationally scored composite scales (ρ = .24). Scales developed to measure conscientiousness and leadership were generally the most predictive of the job performance of the narrow construct domains, and particularly when empirically keyed. However, when biodata scores were correlated with theoretically aligned performance ratings, rational scoring resulted in similar validity coefficients as empirical scoring. Finally, biodata scales exhibited expected patterns of correlations with external measures and were only modestly correlated with cognitive ability and five-factor model personality scores. Taken together, biodata inventories are highly predictive assessment methods and are likely to provide unique variance over other common predictors. 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引用次数: 9
摘要
虽然生物数据清单长期以来一直用于招聘求职者,但目前的生物数据知识有限,当代生物数据元分析评论的方式也很少。本研究通过进行一项更新的元分析,建立了对生物数据有效性的精确理解,该分析从两个重要的定义特征:构建域和评分方法(理性、混合、经验)来区分生物数据有效性。根据工作绩效和额外工作成果的标准相关效度以及与常见外部招聘措施的趋同效度建立了证据。总共检查了180个标准相关性的独立样本,并分析了63个包含收敛度量相关性的样本。荟萃分析的结果显示,生物数据清单是最具预测性的评估方法之一,但与工作成果的关系因构建领域和评分方法而异。经验评分的综合量表的标准相关效度(ρ = 0.44)优于理性评分的综合量表(ρ = 0.24)。为衡量责任心和领导力而开发的量表通常最能预测狭窄结构领域的工作表现,特别是当经验关键时。然而,当生物数据得分与理论一致的绩效评分相关联时,理性评分产生的效度系数与经验评分相似。最后,生物数据量表与外部测量显示出预期的相关性模式,与认知能力和五因素模型人格得分只有适度的相关性。综上所述,生物数据清单是高度预测性的评估方法,可能比其他常见预测指标提供独特的差异。(PsycInfo Database Record (c) 2022 APA,版权所有)。
Meta-analysis of biodata in employment settings: Providing clarity to criterion and construct-related validity estimates.
Although biodata inventories have long been used to hire job applicants, there are limitations to current biodata knowledge and little in the way of contemporary biodata meta-analytic reviews. This study establishes a precise understanding of biodata validity by conducting an updated meta-analysis that differentiates biodata validity in terms of two important defining features: construct domain and scoring method (rational, hybrid, empirical). Evidence was established in terms of criterion-related validity with job performance and additional work outcomes, as well as convergent validity with common external hiring measures. In total, 180 independent samples of criterion correlations were examined, and 63 samples were analyzed containing correlations with convergent measures. Findings across the meta-analyses revealed that biodata inventories are one of the most predictive assessment methods available, but that the relationship with work outcomes differs by construct domain and scoring method. Empirically scored overall composite scales had superior criterion-related validity (ρ = .44) to rationally scored composite scales (ρ = .24). Scales developed to measure conscientiousness and leadership were generally the most predictive of the job performance of the narrow construct domains, and particularly when empirically keyed. However, when biodata scores were correlated with theoretically aligned performance ratings, rational scoring resulted in similar validity coefficients as empirical scoring. Finally, biodata scales exhibited expected patterns of correlations with external measures and were only modestly correlated with cognitive ability and five-factor model personality scores. Taken together, biodata inventories are highly predictive assessment methods and are likely to provide unique variance over other common predictors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).